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01-05-2019 | Cardiac

Coronary CT angiography–derived plaque quantification with artificial intelligence CT fractional flow reserve for the identification of lesion-specific ischemia

Authors: Philipp L. von Knebel Doeberitz, Carlo N. De Cecco, U. Joseph Schoepf, Taylor M. Duguay, Moritz H. Albrecht, Marly van Assen, Maximilian J. Bauer, Rock H. Savage, J. Trent Pannell, Domenico De Santis, Addison A. Johnson, Akos Varga-Szemes, Richard R. Bayer, Stefan O. Schönberg, John W. Nance, Christian Tesche

Published in: European Radiology | Issue 5/2019

Abstract

Objectives

We sought to investigate the diagnostic performance of coronary CT angiography (cCTA)–derived plaque markers combined with deep machine learning–based fractional flow reserve (CT-FFR) to identify lesion-specific ischemia using invasive FFR as the reference standard.

Methods

Eighty-four patients (61 ± 10 years, 65% male) who had undergone cCTA followed by invasive FFR were included in this single-center retrospective, IRB-approved, HIPAA-compliant study. Various plaque markers were derived from cCTA using a semi-automatic software prototype and deep machine learning–based CT-FFR. The discriminatory value of plaque markers and CT-FFR to identify lesion-specific ischemia on a per-vessel basis was evaluated using invasive FFR as the reference standard.

Results

One hundred three lesion-containing vessels were investigated. 32/103 lesions were hemodynamically significant by invasive FFR. In a multivariate analysis (adjusted for Framingham risk score), the following markers showed predictive value for lesion-specific ischemia (odds ratio [OR]): lesion length (OR 1.15, p = 0.037), non-calcified plaque volume (OR 1.02, p = 0.007), napkin-ring sign (OR 5.97, p = 0.014), and CT-FFR (OR 0.81, p < 0.0001). A receiver operating characteristics analysis showed the benefit of identifying plaque markers over cCTA stenosis grading alone, with AUCs increasing from 0.61 with ≥ 50% stenosis to 0.83 with addition of plaque markers to detect lesion-specific ischemia. Further incremental benefit was realized with the addition of CT-FFR (AUC 0.93).

Conclusion

Coronary CTA–derived plaque markers portend predictive value to identify lesion-specific ischemia when compared to cCTA stenosis grading alone. The addition of CT-FFR to plaque markers shows incremental discriminatory power.

Key Points

• Coronary CT angiography (cCTA)–derived quantitative plaque markers of atherosclerosis portend high discriminatory power to identify lesion-specific ischemia.

• Coronary CT angiography–derived fractional flow reserve (CT-FFR) shows superior diagnostic performance over cCTA alone in detecting lesion-specific ischemia.

• A combination of plaque markers with CT-FFR provides incremental discriminatory value for detecting flow-limiting stenosis.

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Title: Coronary CT angiography–derived plaque quantification with artificial intelligence CT fractional flow reserve for the identification of lesion-specific ischemia
Authors: Philipp L. von Knebel Doeberitz
Carlo N. De Cecco
U. Joseph Schoepf
Taylor M. Duguay
Moritz H. Albrecht
Marly van Assen
Maximilian J. Bauer
Rock H. Savage
J. Trent Pannell
Domenico De Santis
Addison A. Johnson
Akos Varga-Szemes
Richard R. Bayer
Stefan O. Schönberg
John W. Nance
Christian Tesche
Publication date: 01-05-2019
Publisher: Springer Berlin Heidelberg
Published in: European Radiology / Issue 5/2019
Print ISSN: 0938-7994
Electronic ISSN: 1432-1084
DOI: https://doi.org/10.1007/s00330-018-5834-z

At a glance: The STEP trials

Springer Medicine

Coronary CT angiography–derived plaque quantification with artificial intelligence CT fractional flow reserve for the identification of lesion-specific ischemia

Abstract

Objectives

Methods

Results

Conclusion

Key Points

At a glance: The STEP trials

Springer Medicine

Abstract

Objectives

Methods

Results

Conclusion

Key Points

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